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        <span>OUC软工第1组</span>
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        <h2>SAR图像变化检测</h2>
        <p>
            本项目采用Ms-CapsNet网络的高精度SAR图像变化检测算法,对同一地区不同时相<br/>
            的两幅或多幅SAR图像进行分析,准确地检测出其中的变化部分和未变化部分。用户<br/>
            可以快速、准确地进行SAR图像的变化检测,提高对地图变化的监测能力。我们的解<br/>
            决方案不仅高效，而且易于使用，使用户能够轻松地访问和利用我们的服务。<br/>
            <br/><br/><br/>
            &nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp
            &nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp
            项目成员：路修哲 黄乃煊<br/>
            &nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp
            &nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp
            特别鸣谢：高峰（课任老师） 刘文力（助教）
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            <h2>专业，我们是认真的！</h2>
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                SAFNet网络作为核心算法，结合多尺度卷积、多维主胶囊层和<br/>
                多尺度特征提取的dropout机制,专注为您提供更高的精度和准确性。
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{#            <p>“每周日常”</p>#}
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{#            <p>“制定计划”</p>#}
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